Natural-language search across your library
Indexes media and documents on your Mac so you can search across them in plain English, including queries that work across multiple file types.
GoldenRetriever is a macOS public beta for AI search across videos, audio, and documents in a local media library. It returns sourced answers with timestamps and uses the user's own Gemini API key for AI requests.
GoldenRetriever is a macOS public beta for AI video and audio search across a local media library. It indexes videos, audio, PDFs, slides, screenshots, scans, Word documents, PowerPoints, images, and plain text so users can search by meaning in plain English.
The product's core distinction is that it works from the original media, not just transcripts. The site says it watches video and hears audio, then returns sourced answers with timestamps, while keeping originals on disk and using the user's own Gemini API key for AI requests.
Indexes media and documents on your Mac so you can search across them in plain English, including queries that work across multiple file types.
Understands videos by their visual content, such as slides on screen, demos, and whiteboard sessions, rather than only the spoken transcript.
Processes audio directly so emphasis, tone, and context remain part of the searchable record for podcasts, meetings, coaching sessions, and voice memos.
Supports PDFs, Word documents, PowerPoints, images, and plain text alongside media files, creating one searchable layer across different formats.
Returns sourced answers with timestamps so users can trace a response back to the underlying recording, slide, or document context.
Runs as a macOS public beta and uses the user's own Gemini API key for AI traffic, while original files stay on disk.
Find a specific moment in a recorded meeting, call, or interview by asking for the topic, wording, or decision you remember, then jump back to the timestamped source.
Search across decks, PDFs, screenshots, scans, and notes when you remember the idea but not the file name or folder, and retrieve the relevant document by meaning.
Use the visual context in videos to find slides, whiteboards, demos, or on-screen elements that a transcript would miss.
Work through podcasts, lectures, coaching sessions, and voice memos by searching the spoken content plus the audio signal's broader context.
Ask across mixed archives for a single answer that may span a training video, slide deck, and voice memo, then verify each part from the cited sources.
GoldenRetriever indexes media and documents on a Mac and lets you ask questions in plain English. It returns sourced answers with timestamps so you can jump back to the original moment or file.
The source material says it is a public beta for macOS. The home page invites users to download the beta on Mac.
The home page says it works with videos, audio, PDFs, slides, screenshots, scans, Word documents, PowerPoints, images, and plain text.
The product says AI traffic uses the user's own Gemini API key, billed by Google directly. It also says originals stay on disk.
The site says you can ask questions across everything you have and receive answers with sources and timestamps, rather than relying only on transcripts.
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